comparing applications with "lines of code" is okay for laymen to do but software engineers know the challenge at hand to let an AI model build a chrome like codebase (https://github.com/chromium/chromium).

LLMs are good now, they can do miniscule things on a smaller context. what we need now is a bigger thinking machine that gets the big picture and makes use of LLM and other predictive networks to get things done while being focused on the big picture and bug fixes along the way. "bugs" are not just errors that the super intelligent AI will never make, but also adjustments and adaptations to technological improvements and improved algorithms.

but we can totally do the #lines of code vs tokens ->> LLM thing, it's a fun mental exercise but pointless.